

from __future__ import annotations

lowerCAmelCase_			      =      list[tuple[int, int]]

lowerCAmelCase_			      =      [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

lowerCAmelCase_			      =      ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right





class       snake_case_  :







			'''simple docstring'''

			def __init__(	self					:							List[Any]				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							float				,  _UpperCamelCase					:							Node | None				,  ) ->List[str]:
									snake_case_  =      pos_x
									snake_case_  =      pos_y
									snake_case_  =      (pos_y, pos_x)
									snake_case_  =      goal_x
									snake_case_  =      goal_y
									snake_case_  =      g_cost
									snake_case_  =      parent
									snake_case_  =      self.calculate_heuristic()







			def 							snake_case__(	self					:							Optional[Any]				) ->float:
									snake_case_  =      abs(self.pos_x - self.goal_x				)
									snake_case_  =      abs(self.pos_y - self.goal_y				)
									return dx + dy







			def __lt__(	self					:							str				,  _UpperCamelCase					:							Tuple				) ->bool:
									return self.f_cost < other.f_cost






class       snake_case_  :







			'''simple docstring'''

			def __init__(	self					:							int				,  _UpperCamelCase					:							tuple[int, int]				,  _UpperCamelCase					:							tuple[int, int]				) ->Optional[int]:
									snake_case_  =      Node(start[1]				,  start[0]				,  goal[1]				,  goal[0]				,  0				,  _UpperCamelCase				)
									snake_case_  =      Node(goal[1]				,  goal[0]				,  goal[1]				,  goal[0]				,  9_9_9_9_9				,  _UpperCamelCase				)

									snake_case_  =      [self.start]
									snake_case_  =      []

									snake_case_  =      False







			def 							snake_case__(	self					:							Tuple				) ->Path | None:
									while self.open_nodes:
															# Open Nodes are sorted using __lt__
															self.open_nodes.sort()
															snake_case_  =      self.open_nodes.pop(0				)

															if current_node.pos == self.target.pos:
																					snake_case_  =      True
																					return self.retrace_path(_UpperCamelCase				)

															self.closed_nodes.append(_UpperCamelCase				)
															snake_case_  =      self.get_successors(_UpperCamelCase				)

															for child_node in successors:
																					if child_node in self.closed_nodes:
																											continue

																					if child_node not in self.open_nodes:
																											self.open_nodes.append(_UpperCamelCase				)
																					else:
																											# retrieve the best current path
																											snake_case_  =      self.open_nodes.pop(self.open_nodes.index(_UpperCamelCase				)				)

																											if child_node.g_cost < better_node.g_cost:
																																	self.open_nodes.append(_UpperCamelCase				)
																											else:
																																	self.open_nodes.append(_UpperCamelCase				)

									if not self.reached:
															return [self.start.pos]
									return None







			def 							snake_case__(	self					:							Union[str, Any]				,  _UpperCamelCase					:							Node				) ->list[Node]:
									snake_case_  =      []
									for action in delta:
															snake_case_  =      parent.pos_x + action[1]
															snake_case_  =      parent.pos_y + action[0]

															if not (0 <= pos_x <= len(grid[0]				) - 1 and 0 <= pos_y <= len(_UpperCamelCase				) - 1):
																					continue

															if grid[pos_y][pos_x] != 0:
																					continue

															successors.append(
															    Node(
															        _UpperCamelCase				,  _UpperCamelCase				,  self.target.pos_y				,  self.target.pos_x				,  parent.g_cost + 1				,  _UpperCamelCase				,  )				)
									return successors







			def 							snake_case__(	self					:							Any				,  _UpperCamelCase					:							Node | None				) ->Path:
									snake_case_  =      node
									snake_case_  =      []
									while current_node is not None:
															path.append((current_node.pos_y, current_node.pos_x)				)
															snake_case_  =      current_node.parent
									path.reverse()
									return path


if __name__ == "__main__":
					lowerCAmelCase_			      =      (0, 0)
					lowerCAmelCase_			      =      (len(grid) - 1, len(grid[0]) - 1)
					for elem in grid:
										print(elem)

					print('''------''')

					lowerCAmelCase_			      =      GreedyBestFirst(init, goal)
					lowerCAmelCase_			      =      greedy_bf.search()
					if path:
										for pos_x, pos_y in path:
															lowerCAmelCase_			      =      2

										for elem in grid:
															print(elem)


from random import randint
from tempfile import TemporaryFile

import numpy as np


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__):

			'''simple docstring'''



			a_						:						List[Any] 							= 0
			if start < end:
						a_						:						Dict 							= randint(a__  ,	a__)
						a_						:						List[str] 							= a[end]
						a_						:						Tuple 							= a[pivot]
						a_						:						Tuple 							= temp

						a_							,					a_						:						List[Any] 							= _in_place_partition(a__  ,	a__  ,	a__)
						count += _in_place_quick_sort(a__  ,	a__  ,	p - 1)
						count += _in_place_quick_sort(a__  ,	p + 1  ,	a__)
			return count


def 					_UpperCAmelCase				(						a__  ,	a__  ,	a__):

			'''simple docstring'''



			a_						:						Optional[int] 							= 0
			a_						:						Union[str, Any] 							= randint(a__  ,	a__)
			a_						:						Union[str, Any] 							= a[end]
			a_						:						Any 							= a[pivot]
			a_						:						Any 							= temp
			a_						:						int 							= start - 1
			for index in range(a__  ,	a__):
						count += 1
						if a[index] < a[end]:  # check if current val is less than pivot value
									a_						:						str 							= new_pivot_index + 1
									a_						:						Optional[Any] 							= a[new_pivot_index]
									a_						:						str 							= a[index]
									a_						:						Union[str, Any] 							= temp

			a_						:						Union[str, Any] 							= a[new_pivot_index + 1]
			a_						:						Tuple 							= a[end]
			a_						:						Any 							= temp
			return new_pivot_index + 1, count


__snake_case				:      Union[str, Any]   		=			TemporaryFile()
__snake_case				:      Dict   		=			1_00  # 1000 elements are to be sorted


__snake_case		, __snake_case				:      int   		=			0, 1  # mean and standard deviation
__snake_case				:      Tuple   		=			np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("""The array is""")
print(X)


outfile.seek(0)  # using the same array
__snake_case				:      str   		=			np.load(outfile)
__snake_case				:      Dict   		=			len(M) - 1
__snake_case				:      Dict   		=			_in_place_quick_sort(M, 0, r)

print(
    """No of Comparisons for 100 elements selected from a standard normal distribution"""
    """is :"""
)



print(z)


